About Systematic Reviews
Does a Systematic Review Need a Meta-Analysis
Although systematic reviews and meta-analyses overlap, they’re different in methodology and purpose. Additionally, you don’t always need one to complete the other. A systematic review doesn’t need a meta-analysis; that said, a meta-analysis is always done in the context of different types of systematic reviews.
What Is A Systematic Review?
A systematic review is a rigorous methodology that involves identifying, selecting, evaluating, and synthesizing high-quality primary studies to answer a focused research question. It’s considered the highest level of evidence due to its comprehensive and balanced nature as it requires researchers to provide an exhaustive summary of published and unpublished literature to derive their results.
Completing a systematic review is a time-consuming and laborious process, and it implores researchers to know how to create protocols, enforce eligibility criteria, and organize a systematic review. That said, nowadays, researchers have an easier time doing them thanks to software, technology, and tools such as critical appraisal tools, literature review software like DistillerSR, and other tools that reduce the risk of bias for systematic reviews.
What Is A Meta-Analysis?
A meta-analysis is a statistical procedure used to summarize data from multiple studies. It’s done in the context of systematic reviews, representing a specialized subset. In other words, a meta-analysis is simply an approach done within a systematic review to combine the data derived for it.
Not all systematic reviews include a meta-analysis. However, all meta-analyses are found in systematic reviews.
A meta-analysis is a statistical procedure for combining numerical data from multiple separate studies. A meta-analysis should only ever be conducted in the context of a systematic review.
What Does A Meta-Analysis Do?
Conclusions produced by meta-analysis are statistically stronger than the analysis of any single study, due to increased numbers of subjects, greater diversity among subjects, or accumulated effects and results.
It goes beyond critique and integration and conducts an objective secondary analysis of the studies included in a systematic review. The procedure is used to identify a common effect when the effect size (treatment effect) is consistent from one study to the next.
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Systematic Reviews without Meta-Analyses
It’s not always necessary to include a meta-analysis in a systematic review. Here are some situations in which they won’t be needed.
When Qualitative Data Can Better Answer the Research Question
Meta-analyses often deal with numerical data. If a research question can be better answered with qualitative data (e.g. research questions that ask “How?”), then it can be done without a meta-analysis.
When Studies Are Too Dissimilar
It doesn’t make sense to do a meta-analysis on studies that are too dissimilar, since you won’t be able to derive a cohesive resolution. In these cases, it may be better to conduct another synthesis method (e.g. narrative synthesis), instead.
When the Methodological Quality of the Studies Is Poor
If the methodological qualities of selected studies are sub-par (e.g. the participants of the studies aren’t sufficiently randomized), then it’s inappropriate to conduct a meta-analysis since this would yield misleading results.
When Data Is Insufficient
Not all systematic reviews yield enough evidence to allow a meta-analysis to even be considered in the first place. In cases like these, researchers should explore other strategies for synthesis and reporting.
Systematic reviews don’t always need meta-analyses. Determining whether or not it’s necessary depends on your research question, the data you’ve gathered, and your review protocol.
Proper planning can help guide this decision as it arises down the road, so make sure that you take the time to define your methodology and analytical approach before you set out on conducting your systematic review.